Modeling Diphtheria Transmission and Control Strategies in Nigeria using A Compartmental Model Approach

Diphtheria remains a public health challenge in many settings, especially where vaccination coverage is incomplete and infections go undetected. A key challenge in controlling the disease is the often-overlooked role of asymptomatic individuals, who can silently sustain transmission. This study aims to develop a diphtheria vaccine treatment model to describe the transmission dynamics of diphtheria within the Nigerian population and to evaluate the impact of different vaccination scenarios and treatments on preventing and controlling diphtheria. Reported diphtheria cases in Nigeria were obtained from the Nigeria Centre for Disease Control (NCDC) and used to estimate the model's parameters. We computed the basic reproduction number and received a mean value of the basic reproduction number (\(\:{R}_{0}\)) = 6.010, suggesting that diphtheria transmission can only be brought under control when existing interventions are improved. The sensitivity analysis identified key parameters that govern the transmission dynamics of diphtheria. Numerical solutions further showed that higher transmission rates rapidly reduce the susceptible population and intensify epidemics. In contrast, high vaccination coverage, timely completion of vaccine schedules, low immunity waning, and prompt treatment markedly reduce infections. While partial vaccination offers short-term protection, it is insufficient for long-term disease control without full immunization. The findings of this study reiterate the need for control strategies that go beyond symptomatic case management to include sustained vaccination, booster doses, and targeted efforts to limit asymptomatic transmission. The model offers practical insights to support evidence-based diphtheria control policies, particularly in resource-limited settings.